7 accepted papers
Imitation learning (IL) for end-to-end autonomous driving (E2E-AD) has made great progress recently in the closed-loop evaluation of the CARLA simulator. However, the causal confusion remains an open problem. To address this issue, we propose the BEVDrive-E2E to explore the interpretability of the e
We propose a Visual Place Recognition (VPR) framework by sharing lightweight keypoint extraction modules for local features. Current research on the joint learning of local keypoint matching and VPR is relatively scarce, and the application deployment of real-time spatial computing on edge devices h
Correspondence matching is a fundamental and crucial task in robot vision. In recent years, deep learning-based keypoint matching techniques have shown outstanding performance in downstream tasks. Conventional learning-based correspondence matching methods rely on large datasets and a specific train
Monocular Bird’s Eye View (BEV) semantic segmentation is critical for autonomous driving for its inherent advantages in spatial representation and downstream tasks. However, it is challenging to simultaneously learn view transformation and pixel-wise classification. Previous works suffer from non-fl…
In the context of 3D scene perception tasks, the significance of 3D occupancy prediction has been progressively growing, aiming to forecast the occupancy state of voxels in a discrete 3D space. However, existing methods typically exhibit several limitations, such as restricted adaptability to non-pi…
"Search for" or "Navigate to"? When we find a specific object in an unknown environment, the two choices always arise in our subconscious mind. Before we see the target, we search for the target based on prior experience. Once we have seen the target, we can navigate to it by remembering the target…
Stereo matching is a common technique used in 3D perception, but transparent objects such as reflective and penetrable glass pose a challenge as their disparities are often estimated inaccurately. In this paper, we propose transparency-aware stereo (TA-Stereo), an effective solution to tackle this i…